Dhiana Deva
Data AnalystMLOps @ Neko
Neko Health
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
MLOps @ Neko
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with lean and agile generalist background from experiences in CERN, Accenture, ThoughtWorks, Spotify, EQT and Neko Health. Other than ML, Data and Software Engineering, Diversity and Inclusion is also an area of demonstrated leadership.
Universidade Federal do Rio de Janeiro
Engineer's Degree, Electronics and Computer Engineering
January 1, 2006 – Present
Neko Health
ML Engineering Lead, MLOps
February 1, 2025 – Present
Stockholm, Stockholm County, Sweden
EQT Group
Staff Machine Learning Engineer
March 1, 2023 – February 1, 2025
EQT Group
Senior Machine Learning Engineer
April 1, 2020 – March 1, 2023
Spotify
Senior Machine Learning Engineer
August 1, 2019 – February 1, 2020
Spotify
Machine Learning Engineer
January 1, 2018 – July 1, 2019
Spotify
Software Developer
May 1, 2016 – January 1, 2018
ThoughtWorks
Senior Consultant
July 1, 2015 – April 1, 2016
Greater São Paulo Area
University of West Bohemia, Pilsen
Undergraduate Researcher
January 1, 2015 – March 1, 2015
Czechia
Concrete Solutions
Software Developer
April 1, 2011 – March 1, 2015
Greater Rio de Janeiro
CERN
Undergraduate Researcher
January 1, 2011 – April 1, 2011
Switzerland
Laboratório de Processamento de Sinais - UFRJ
Undergraduate Researcher
May 1, 2009 – April 1, 2011
Laboratório de Processamento de Sinais - UFRJ
Undergraduate Researcher
May 1, 2008 – May 1, 2009
Departamento de Eletrônica e Computação - DEL/POLI/UFRJ
Undergraduate Intern
May 1, 2007 – May 1, 2008
Greater Rio de Janeiro
Introduction to Neuroeconomics: how the brain makes decisions
Coursera
June 24, 2026 – Present
Microeconomics Principles
Coursera
June 24, 2026 – Present
TOEFL ITP
ETS
June 24, 2026 – Present
Introduction to Data Science
Coursera
June 24, 2026 – Present
Model Thinking
Coursera
June 24, 2026 – Present
Developing Innovative Ideas for New Companies: The First Step in Entrepreneurship
Coursera
June 24, 2026 – Present
Introduction to Artificial Intelligence
Udacity
June 24, 2026 – Present
Core Concepts in Data Analysis
Coursera
June 24, 2026 – Present
Professional Scrum Master
Scrum.org
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Advanced Competitive Strategy
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse professional background, working in various companies from large tech (Spotify, EQT Group) to consulting (ThoughtWorks) and research institutions (CERN, UFRJ). Their involvement in D&I initiatives at Spotify suggests a commitment to inclusive work environments. The breadth of experience, including leading teams and driving strategic initiatives, indicates a proactive and influential individual. However, the target role is 'Data Analyst', which is a significant shift from their extensive Machine Learning Engineering and MLOps leadership experience. While they have a strong data background, the direct alignment with a pure Data Analyst role, which typically focuses more on reporting, dashboards, and business intelligence rather than ML model development and MLOps, is not immediately clear from the provided data. This could indicate a potential mismatch in expectations or a desire for a career pivot.
Soft Skills & Operational Fit
The candidate's resume indicates strong leadership skills, experience in setting strategy, and a history of driving adoption of new practices (MLOps, LLMOps). Participation in Diversity and Inclusion initiatives suggests good collaboration and cultural awareness. The experience in various roles from software developer to ML Engineering Lead demonstrates adaptability and a growth mindset. However, without psychometric test results, a full assessment of work attitude, stress handling, and team collaboration is not possible.